37 Interactive Technology Team
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37 Interactive Technology Team

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37 Interactive Technology Team
37 Interactive Technology Team
Sep 25, 2023 · Cloud Native

Investigation of Kubernetes Container Isolation Mechanism and Its Impact

The article investigates a cloud‑vendor Kubernetes isolation feature that inserts iptables DROP rules into a pod’s network namespace, demonstrating how it fully blocks traffic, triggers liveness‑probe restarts, and impacts services depending on replica count and probe configuration, while preserving state only without probes.

Container SecurityKubernetesLivenessProbe
0 likes · 7 min read
Investigation of Kubernetes Container Isolation Mechanism and Its Impact
37 Interactive Technology Team
37 Interactive Technology Team
Sep 18, 2023 · Product Management

How to Build, Productize, and Iterate an Analytical Data Product

The guide explains how to create an analytical data product by first defining the business scenario and KPI, selecting and abstracting an analysis framework into reusable modules, visualizing core metrics across dimensions, and continuously iterating through cold‑start, promotion, and maintenance phases to keep the product aligned with evolving business needs.

AnalyticsData ProductFramework
0 likes · 18 min read
How to Build, Productize, and Iterate an Analytical Data Product
37 Interactive Technology Team
37 Interactive Technology Team
Sep 7, 2023 · Cloud Native

Design and Implementation of the kjob Asynchronous Task Scheduling Platform on Kubernetes

The 37Game team built the cloud‑native kjob platform to replace VM‑based schedulers, providing a unified, highly available Kubernetes solution that manages both CronJob‑style scheduled tasks and long‑running Deployments through a backend‑agent architecture, offering CRUD operations, rich configuration, real‑time monitoring, alerting, and seamless migration.

Asynchronous JobsCloud-nativeGo
0 likes · 15 min read
Design and Implementation of the kjob Asynchronous Task Scheduling Platform on Kubernetes
37 Interactive Technology Team
37 Interactive Technology Team
Aug 23, 2023 · Artificial Intelligence

LoRA Model Training Guide for Stable Diffusion: Comparison, Workflow, and Tips

This guide compares Stable Diffusion fine‑tuning methods, shows why LoRA offers the best size‑and‑speed trade‑off, and provides a step‑by‑step workflow—from dataset collection and preprocessing to parameter tuning, 20‑minute training on a single GPU, and practical tips for successful custom model generation.

AI artDreamBoothImage Generation
0 likes · 9 min read
LoRA Model Training Guide for Stable Diffusion: Comparison, Workflow, and Tips
37 Interactive Technology Team
37 Interactive Technology Team
Aug 7, 2023 · Mobile Development

Understanding and Analyzing Android ANR (Application Not Responding)

Android ANR occurs when the UI thread is blocked, triggered by time‑outs such as KeyDispatch, Broadcast, Service or ContentProvider, often caused by long I/O, deadlocks, Binder calls or resource exhaustion; diagnosing involves examining traces.txt, thread states, CPU/memory metrics, and using tools like Looper logs, Choreographer, or Tencent Matrix to prevent future freezes.

ANRAndroidCPU
0 likes · 26 min read
Understanding and Analyzing Android ANR (Application Not Responding)
37 Interactive Technology Team
37 Interactive Technology Team
Jul 26, 2023 · Backend Development

Investigation and Resolution of CPU Spike in a Kafka-Go Consumer Using pprof

Using Go’s pprof, the team traced a gradual CPU spike in a high‑throughput kafka‑go consumer to a saturated commit queue and repeatedly nested context values, which forced costly lookups; eliminating the unnecessary trace‑id context injection (or recreating a fresh context each loop) resolved the issue and reduced CPU usage to under 2 %.

ConsumerGoKafka
0 likes · 10 min read
Investigation and Resolution of CPU Spike in a Kafka-Go Consumer Using pprof
37 Interactive Technology Team
37 Interactive Technology Team
Jul 21, 2023 · Cloud Native

Automated Performance Testing Architecture Using Alibaba Cloud PTS

The article explains how automated performance testing using Alibaba Cloud PTS—integrated with VPC‑based Kubernetes clusters, GitLab CI/CD pipelines, and cloud APIs—overcomes the inaccuracy, coordination delays, and resource waste of manual testing by providing on‑demand, scalable load generation, scenario orchestration, real‑time metrics, and cost‑effective reporting.

Alibaba Cloud PTSCI/CDDevOps
0 likes · 4 min read
Automated Performance Testing Architecture Using Alibaba Cloud PTS
37 Interactive Technology Team
37 Interactive Technology Team
Jul 4, 2023 · Cloud Native

Understanding the Removal of Dockershim in Kubernetes v1.24 and Its Alternatives

Starting with Kubernetes v1.24 the built‑in dockershim is removed, requiring users to switch to a CRI‑compatible runtime such as containerd or CRI‑O—or install cri‑dockerd for Docker compatibility—while updating scripts, logs, and tooling, and using crictl or ctr for debugging and managing containers and pods.

CRIDockershimKubernetes
0 likes · 12 min read
Understanding the Removal of Dockershim in Kubernetes v1.24 and Its Alternatives
37 Interactive Technology Team
37 Interactive Technology Team
Jun 15, 2023 · Backend Development

Concurrent Safety of Go Maps: Issues, Solutions, and Performance Comparison

Go maps are not safe for concurrent access, so programs can panic when multiple goroutines read and write the same map; to prevent this you can use sync.Once for immutable data, protect maps with sync.RWMutex, employ sharded locks via concurrent‑map, or use the built‑in sync.Map, each offering different performance trade‑offs depending on read/write ratios and concurrency level.

GoRWMutexconcurrency
0 likes · 13 min read
Concurrent Safety of Go Maps: Issues, Solutions, and Performance Comparison
37 Interactive Technology Team
37 Interactive Technology Team
May 22, 2023 · Mobile Development

Gradle Build Optimization for Android Projects: Analysis, Debugging, and Configuration

The article demonstrates a systematic approach to speeding up large Android Gradle builds by inspecting logs, stack traces, debugging plugins, profiling task execution with a custom plugin, and applying on‑demand configuration, caching, incremental and parallel compilation settings, which together cut build time by roughly 40 %.

AndroidCachingGradle
0 likes · 12 min read
Gradle Build Optimization for Android Projects: Analysis, Debugging, and Configuration